Spatial high-resolution socio-energetic data for municipal energy system analyses

Area of Science:

• Energy Systems Analysis
• Renewable Energy Research
• Spatial Data Science

Background:

• Municipalities are key actors in the energy transition, needing socio-energetic data for planning.
• Existing data is fragmented, hindering comprehensive municipal energy system analyses.
• The need for localized data is critical for effective renewable energy deployment strategies.

Purpose of the Study:

• To create a unified dataset of socio-energetic indicators for all German municipalities.
• To provide essential input data for municipal energy system analyses and research.
• To facilitate the development of data-driven energy transition strategies at the local level.

Main Methods:

• Compilation of 40 distinct socio-energetic indicators.
• Integration of census, mobility, and renewable energy potential data.
• Geospatial allocation of public data to 11,131 German municipalities.

Main Results:

• A comprehensive dataset covering all German municipalities is now available.
• The dataset includes indicators on population density, vehicle numbers, and wind energy potential.
• A novel municipality typology and grouping based on the data have been developed and included.

Conclusions:

• The compiled dataset is a valuable resource for energy transition research.
• It enables detailed analysis of municipal energy systems and renewable energy potentials.
• The data supports informed decision-making for local energy planning and policy development.